Abstract

The rise of generative artificial intelligence is posing unprecedented challenges to higher education assessment systems. AI’s ability to outperform students in traditional examinations without being detected has exposed the inadequacies of current competency measurement methods, which remain overly focused on monitoring and detecting AI use rather than improving assessment design itself. This article synthesises the latest research to clarify the challenges that generative AI presents to conventional assessment methods. At the same time, it also proposes theoretical frameworks and necessary conditions for redesigning assessment that emphasises core competencies which AI cannot replace.

Keywords: Academic integrity, assessment, generative AI, higher education, redesign.